PROJECT SUMMARY/ABSTRACT The timely and efficient evaluation of new medical treatment strategies, therapies and devices is critical to improving public health. Ubiquitous data collected in the routine care of patients, including registries, health systems and payers, remain underutilized sources of information that could be used to support clinical trial evaluations of novel medical interventions, but require validation. Through a collaboration involving the Smith Center for Outcomes Research at Beth Israel Deaconess Medical Center, Harvard Clinical Research Institute, the Harvard T.H. Chan School of Public Health, the American College of Cardiology (ACC), Premier, Inc., Symphony Health Solutions and Medtronic, we will combine data from two landmark clinical trial programs - the Dual Antiplatelet Therapy (DAPT) Study and the US CoreValve Trials - with comprehensive national data from registries, health systems and payers, to test several hypotheses central to the future evaluation of cardiovascular therapies. In Aim 1, we will test the hypothesis that trial outcomes derived from linked registry, hospital, and claims data will be equivalent to outcomes obtained in clinical trials, suggesting that these alternative data sources can, in some cases, replace traditional clinical trial data. In Aim 2, we will test the hypothesis that information collected through registries, hospitals, and claims that was not collected in the original clinical trial, such as prior non-cardiac hospitalizations and markers of frailty, can augment trial data, through improved risk stratification and identification of heterogeneous treatment effects. In Aim 3, we will leverage the linkage of trials with population-based datasets to enable the creation of novel and broadly applicable metrics to assess overall trial generalizability and applicability to understudied subgroups. The linkage of these diverse resources will create an important opportunity to formally evaluate the strengths and limitations of using non-clinical trial data sources to support and improve clinical trial assessments of medical therapies. The information learned has the potential to greatly inform the future conduct of pragmatic and naturalistic clinical trials, while offering novel insights into the efficacy and safety of therapies to treat coronary and valvular heart disease.